NIH Public Access Otol Neurotol - temporal bone specimen, and a clinically-applicable temporal bone

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  • Robotic Mastoidectomy

    Andrei Danilchenko, B.S., Graduate Student, Dept. of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN

    Ramya Balachandran, Ph.D., Dept. of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN

    Jenna L Toennies, B.S., Graduate Student, Dept. of Mechanical Engineering, Vanderbilt University, Nashville, TN

    Stephan Baron, Dipl.-Ing, Institute of Mechatronic Systems, Leibniz Universitat Hannover, Hanover, Germany

    Benjamin Munske, Institute of Mechatronic Systems, Leibniz Universitat Hannover, Hanover, Germany

    J. Michael Fitzpatrick, Ph.D., Dept. of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN

    Thomas J. Withrow, Ph.D., Dept. of Mechanical Engineering, Vanderbilt University, Nashville, TN

    Robert J Webster III, Ph.D., and Dept. of Mechanical Engineering, Vanderbilt University, Nashville, TN

    Robert F Labadie, M.D., Ph.D., FACS Associate Professor, Dept. of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN

    INTRODUCTION Taylor [1] has proposed that surgical robots be classified as either (a) surgical-assist devices, which modulate a surgeon’s motions, or (b) autonomous robots (which he calls “Surgical CAD/CAM” systems to illustrate the analogy to industrial computer-aided design and manufacturing), which are programmed to replace a portion of the surgical task. Perhaps the most widely known example of a surgical-assist system is the da Vinci® Surgical System (Intuitive Surgical Inc., Sunnyvale, CA, USA), which mimics and modifies the surgeon’s motions. These modifications can include elimination of tremor and scaling of motions such that large motions by the surgeon can be duplicated in a much smaller surgical field. This system has been most heavily used in urologic surgery [2]. Within the field of otolaryngology, it has been implemented for tongue-based resections to avoid splitting the mandible for access [3].

    Of autonomous robots, the ROBODOC® System (Integrated Surgical Systems, Davis, CA, USA) is the most widely used and referenced. This system was designed to bore a receiving lumen for orthopedic reconstructive joint surgery and has been used in more than 20,000 cases. In practice, the device is rigidly affixed to the long bone for the procedure. While it

    Corresponding Author Details: Ramya Balachandran, Ph.D., Research Assistant Professor, Department of Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, 1215 21st Avenue South, 10450 Medical Center, East South Tower, Nashville, TN 37232, ramya.balachandran@vanderbilt.edu, Phone: 615-322-5550, Fax: 615-936-5515.

    NIH Public Access Author Manuscript Otol Neurotol. Author manuscript; available in PMC 2012 January 1.

    Published in final edited form as: Otol Neurotol. 2011 January ; 32(1): 11–16. doi:10.1097/MAO.0b013e3181fcee9e.

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  • was shown that this system can accomplish the task better than a human operator, a class- action law suit was brought in Europe claiming that the wider surgical exposure necessary for the rigid linkage of the robot to the patient led to various complications including muscle and nerve damage, bone dislocation, and chronic pain. Because of these legal troubles, the company ceased operations in 2005 and was acquired by Curexo Medical Technologies (Freemont, CA), who received FDA approval for the ROBODOC® in 2008. The clinical status of the ROBODOC® is in question at the time of this writing.

    Because surgical-assist devices are controlled directly by human manipulation, regulatory approval is more straightforward, and they have been first to achieve widespread clinical adoption. Since autonomous robots are not widely commercially available for surgical applications, few surgeons have any experience with them whatsoever. The surgical-assist device has the advantage of continuous human control, but the disadvantage that it cannot function appropriately unless the controlling human maintains continuous visual access both to the anatomy being resected and to those critical structures in the vicinity of the resection that are to be spared. The autonomous robot by contrast (which is also usually subject to continuous monitoring by the surgeon), relies on the human operator only as a backup while it follows the path prescribed by pre-operative planning. That planning, which can be performed in the surgeon’s office before the patient is brought to the operating room, is based on three-dimensional tomographic images, and as a result, the autonomous robot can resect tissue that remains invisible to the human controller, whose role is primarily to stop the process if a technical problem develops.

    This scenario, in which preplanning determines the path followed by an autonomous robot, is well-suited for procedures involving rigid tissues such as bone. It is much more challenging to implement any degree of autonomy in robotic procedures involving soft tissues because of their deformation between imaging and intervention, but strategies for doing so are the topic of active research in the engineering community. As these results mature and are brought to clinical use, it is likely that we will see a blurring of the line between surgical-assist devices and autonomous robots, as limited autonomy is introduced to the former, while increasing levels of human control are incorporated into the latter. Regardless of the type or classification of robot used, the intent of incorporating robotic technology into a surgical procedure is to produce a better outcome, which can take the form of many metrics including decreased operative time, improved accuracy, smaller incision, decreased recovery time, or overall decreased cost.

    In the field of otology, a core component of otological cases is the mastoidectomy, in which bone is milled away exposing but not damaging vital anatomy. Mastoidectomy lends itself to an autonomous robotic approach for two reasons: (a) the tissue to be resected is encased in rigid bone, and (b) critical anatomical features remain hidden until they are revealed by ablation. The first of these two reasons makes surgery with the autonomous robot feasible; the second makes it useful. The rigidity of bone is essential because it ensures that the three- dimensional structure of the target anatomy is the same during pre-operative imaging and planning as it is during subsequent intervention. The presence of critical hidden anatomy (nerves and other structures that must be spared but are embedded in the bone), exploits the utility of the autonomous robot, because three-dimensional imaging pinpoints the positions of subsurface structures whose general locations can only be estimated during incremental, manual human intervention. As a result, the robot, guided by images that see beneath the surface, can safely ablate bone to which the human operator would be blind.

    Once we have chosen a surgical situation, like the mastoidectomy, in which rigid bone comprises the target and critical anatomy is hidden from view, the central issue in autonomous robotics becomes the accurate determination of the single point in the three-

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  • dimensional pre-operative image that corresponds to a point in the surgical field, and vice versa. This determination of corresponding points in two spaces is termed “registration”, and the success of the robotic approach hinges on the accuracy of registration from the space of the pre-operative tomographic image to the space of the intra-operative patient. This problem is not new. It has, for example, been faced for decades by stereotactic surgeons and others who have provided geometrical guidance intra-operatively based on pre-operative images [4]. To achieve it, an autonomous robot must register these two spaces either through rigid fixation, as is done by the stereotactic frame and by ROBODOC®, or via optical or magnetic tracking, such as that achieved with image-guided surgical (IGS) systems via the alignment of skin surfaces or fiducial markers.

    In this paper, we describe the use of an autonomous robot to perform a mastoidectomy using infrared tracking to monitor the motion of both the specimen and the robot. The method is applied to cadaveric temporal bone specimens. To accomplish this task, fiducial markers were implanted in the specimens, which were subsequently CT scanned. A surgeon identified the boundaries of the mastoid on the CT scan, and the robot was then programmed to mill out the mastoid according to those boundaries. With both the robot and the specimen being tracked, any movement of the specimen during ablation was continuously compensated for by corrective motions of the robot. While the robot is subject to human control via a manual emergency stop button, it otherwise operates completely autonomously. To the best of our knowledge, this is first report of an autonomous robot performing a mastoidectomy.

    MATERIALS AND METHODS Our goal is to successfully develop an autonomous robot system that can mill the regions identified by the surgeon in a CT scan. To achieve this goal, we developed the OTOBOT™ system (Figure 1), which incorporates an industrial robot, the Mitsubishi RV-3S (Mitsubishi Electric & Electronics USA, Inc., Cyprus, CA), controlled by custom software written in Matlab® and Simulink (The MathWorks Inc., Natick, MA) with real-time feedback of the robot’s mo